Sustainable Energy Technologies and Assessments最新文献

{"title":"Corrigendum to “Application of hybrid nanofluid and a twisted turbulator in a parabolic solar trough collector: Energy and exergy models” [Sustain. Energy Technol. Assess. 49 (2022) 101708]","authors":"Yacine Khetib , Ali Alzaed , Ahmad Alahmadi , Goshtasp Cheraghian , Mohsen Sharifpur","doi":"10.1016/j.seta.2024.104102","DOIUrl":"10.1016/j.seta.2024.104102","url":null,"abstract":"","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"72 ","pages":"Article 104102"},"PeriodicalIF":7.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142748430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence and machine learning models application in biodiesel optimization process and fuel properties prediction","authors":"Muhammad Arif ,&nbsp;Adel I. Alalawy ,&nbsp;Yuanzhang Zheng ,&nbsp;Mostafa Koutb ,&nbsp;Tareq Kareri ,&nbsp;El-Sayed Salama ,&nbsp;Xiangkai Li","doi":"10.1016/j.seta.2024.104097","DOIUrl":"10.1016/j.seta.2024.104097","url":null,"abstract":"<div><div>Inefficient transesterification, low-quality fuel properties, and high resource consumption are the bottlenecks associated with conventional biodiesel production. The current research trends include the application of artificial intelligence (AI) and machine learning (ML) to optimize the biodiesel process for improved yield and fuel quality. Previous reviews discussed the applications of ML in the optimization of transesterification parameters and fuel properties. However, there is a lack of deep discussion on feedstock selection, optimization, process monitoring, and cost analysis. The challenges during biodiesel production, ML model selection, and assessment of plant and animal lipid potential for biodiesel under different conditions using AI tools are reviewed. All the parameters that affect biodiesel yield and fuel properties through ML, the efficiency of different models, and pilot-scale techno-economic analyses are also discussed. Biodiesel production from animal and plant lipids showed high yield potential ranging from 78-99 %. ML models demonstrated higher efficacy in transesterification optimization to attain &gt; 90 % yield. Various AI models exhibit a predictive efficiency range (R² = 0.85 to 0.99) for yield and fuel qualities. Economic analyses reveal that the choice of feedstock and catalyst significantly impacts final production costs. ML and AI approaches exhibit the potential for improving the biodiesel process.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104097"},"PeriodicalIF":7.1,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal variation in photovoltaic generation efficiency due to bioaerosol particle accumulation","authors":"Kenji Miki ,&nbsp;Shinnosuke Mori","doi":"10.1016/j.seta.2024.104106","DOIUrl":"10.1016/j.seta.2024.104106","url":null,"abstract":"<div><div>Photovoltaic (PV) panels have been developed as a carbon-free, environmentally friendly method of generating energy. However, because PV panels are placed outdoors, the surrounding environment strongly affects the power generation efficiency. In this study, the soiling effect of pollen accumulation on PV panels on the power generation efficiency was calculated. For accuracy, we used the measured transmittance and the reflectance of the pollen grains and quartz panel in the calculation. In addition, airborne <em>Cryptomeria japonica</em> pollen grain concentrations measured at 120 sites across the country were used to estimate the effect of the accumulated pollen grains on PV panels. The seasonal changes in the PV power generation efficiency due to the accumulated <em>C. japonica</em> pollen alone were estimated as about 5 % at most. However, the power generation efficiency changed logarithmically with the pollen size. Therefore, the dominant pollen type is expected to have a major effect on the seasonal change in the power generation efficiency of PV panels.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104106"},"PeriodicalIF":7.1,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of vehicle-to-grid economy based on sustainable development grounded in game theory","authors":"Jingjin Wu ,&nbsp;Qian Sun ,&nbsp;Chuang Li ,&nbsp;Weihao Tang ,&nbsp;Hui Zhang ,&nbsp;Rongnian Tang ,&nbsp;Conghui Han","doi":"10.1016/j.seta.2024.104087","DOIUrl":"10.1016/j.seta.2024.104087","url":null,"abstract":"<div><div>In a vehicle-to-grid (V2G) peaking system based on coordination games, ultimate goal realized a positive total net return in V2G operations, while ensuring that the interests of all stakeholders reached a balanced equilibrium. This study examined the cost and benefit dynamics of BYD (Build Your Dreams) electric vehicles, encompassing electric vehicle users, power grid companies, and power plants, before and after participating in V2G peak load balancing services. Pre-game analysis revealed that power plants led in terms of revenue, significantly surpassing electric vehicle users, whereas grid companies incurred negative net income. An increase in peak load exacerbated the power company’s net loss, posing a significant challenge to V2G’s sustainable development. However, post-game, a cooperative alliance between the power grid company and car users was forged through financial means, with the power grid company and power plants offering invaluable data support through collaborative efforts. The disparity between optimized peak and base load generation costs narrowed to 79% of pre-optimization levels, with a 3.14% reduction in carbon emissions. Furthermore, the implementation of this collaboration strategy can result in a maximum reduction of 9% in the power grid company’s losses and an enhancement of 6.7% in the net revenue of the entire V2G peak-shaving system. Consequently, this strategy significantly promotes the development of V2G operations.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104087"},"PeriodicalIF":7.1,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Residential energy consumption and price forecasting in smart homes based on the internet of energy","authors":"Shijiao Zhao ,&nbsp;SiZhuo Chen ,&nbsp;Theyab R Alsenani ,&nbsp;Badr Alotaibi ,&nbsp;Mohammed Abuhussain","doi":"10.1016/j.seta.2024.104081","DOIUrl":"10.1016/j.seta.2024.104081","url":null,"abstract":"<div><div>Smart home applications require automatic energy management and control of unwanted energy consumption prices using Artificial intelligence techniques. Previously, there were more studies on price forecasting. However, efficient results are still under research. This study introduces real-time residential energy management systems based on the Internet of Energy with a scheduling strategy. The proposed method employs a Gated Recurrent Unit and Bird Swarm Optimizer (GRU-BSO) along with Real-Time Electricity Scheduling (RTES) based on Price Forecasting (PF) for efficient residential energy management. The research emphasises the optimisation algorithm’s ability to minimise energy costs and promote energy conservation, significantly contributing to the field. Price forecasting (PF) is the central objective in distributed energy production. By forecasting the optimal price, this approach can improve the efficiency of power grids and solve issues with microgrid management and planning. It is suggested that the tariffs for shoulder-peak and on-peak hours be determined using the Time of Use (ToU) model. The proposed method also predicts the energy price used in home energy management. The cloud server and MATLAB-implemented microgrid system are linked via a two-level communications network. The current communications level uses the local communication level as a protocol, which uses IP/TCP and MQTT. The study’s proposed scheduling controller successfully achieved energy savings of 17 kW and 47 cents by utilising the proposed method.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104081"},"PeriodicalIF":7.1,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142724008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a rational framework for economic and risk assessment of energy efficiency projects","authors":"Géremi Gilson Dranka ,&nbsp;José Donizetti de Lima ,&nbsp;Dalmarino Setti ,&nbsp;Gilson Adamczuk Oliveira ,&nbsp;Marcelo Gonçalves Trentin ,&nbsp;Tânia Regina Sieminkoski Sirota ,&nbsp;Paula Ferreira","doi":"10.1016/j.seta.2024.104090","DOIUrl":"10.1016/j.seta.2024.104090","url":null,"abstract":"<div><div>Shifting towards a low-carbon and sustainable economy requires both a shift to Renewable Energy Sources (RES) and a significant increase in Energy Efficiency (EE) targets. This paper introduces a novel, user-friendly, and step-by-step framework for the techno-economic and risk-based assessment of EE Projects (FEEP). The four-stage methodology represents a step beyond traditional methods by systematically identifying intervention areas, conducting technical evaluations, and providing a comprehensive tool for economic and risk assessment. The proposed tool may empower decision-makers to select the most suitable approaches for the economic viability analysis of future projects. The framework incorporates environmental assessment, quantifying anticipated CO₂ reductions from EE measures. A real-world case study demonstrates how the new framework allows structuring the decision-making process under a reliable and straightforward approach, providing additional confidence to the investors through visual risk assessment indicators. The paper concludes with how managers and EE analysts of private and public institutions can take advantage of the proposed methodology to evaluate and benchmark a broader range of EE initiatives.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104090"},"PeriodicalIF":7.1,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Convective heat transfer coefficient for realistic turbulence parameters using LES vs. RANS turbulence models in case of free-standing photovoltaic panel","authors":"Ivo Marinić-Kragić ,&nbsp;Mišo Jurčević ,&nbsp;Filip Grubišić-Čabo ,&nbsp;Sandro Nižetić","doi":"10.1016/j.seta.2024.104108","DOIUrl":"10.1016/j.seta.2024.104108","url":null,"abstract":"<div><div>The efficiency of photovoltaic (PV) and hybrid photovoltaic-thermal (PVT) solar panels partly depends on the heat transfer to the ambient air. The exact value of the convective heat transfer coefficient (HTC) is particularly important for the development of cooling techniques. The HTC values are usually determined from experimental data available for flat plates and similar geometries. Since the HTC depends on the geometrical details of the PV panel and the environment, the HTC values are usually estimated using computational fluid dynamics (CFD) based on the Reynolds-averaged Navier-Stokes equations (RANS). In this work, a free-standing PV panel is considered, and the main objective of the work is to compare the RANS results with the large eddy simulation (LES), which is expected to provide more reliable results compared to the available experimental data. The research includes the effects of inlet velocity, turbulence intensity and turbulence length scale. It was shown that the HTC depends on both turbulence intensity and turbulence length scale. The results show that RANS models significantly overestimate the influence of inlet turbulence on the HTC, by up to 70% at high inlet turbulence intensities. Meanwhile, the LES values are within 5 % of the experimental HTC values.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104108"},"PeriodicalIF":7.1,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges and opportunities in Machine learning for bioenergy crop yield Prediction: A review","authors":"Joseph Lepnaan Dayil ,&nbsp;Olugbenga Akande ,&nbsp;Alaa El Din Mahmoud ,&nbsp;Richard Kimera ,&nbsp;Olakunle Omole","doi":"10.1016/j.seta.2024.104057","DOIUrl":"10.1016/j.seta.2024.104057","url":null,"abstract":"<div><div>Bioenergy offers a sustainable alternative to fossil fuels, addressing energy security and climate change concerns. This paper reviews the current landscape of machine learning (ML) applications in predicting bioenergy crop yields. It explores the potential of ML models, such as random forests, support vector machines, and neural networks, to improve yield predictions by analyzing complex agricultural datasets, including soil quality, weather conditions, and crop characteristics. The review highlights the challenges of implementing ML in bioenergy systems, such as data limitations, model interpretability, and scalability. Key findings indicate that integrating ML with traditional agricultural practices can optimize resource allocation, enhance yield predictions, and promote more sustainable bioenergy production. The paper also discusses future research directions for improving ML techniques to advance bioenergy crop yield prediction and sustainability.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104057"},"PeriodicalIF":7.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability performance of pumped-storage units considering elastic water hammer effects in pressurized piping systems: Mechanism analysis and quantitative criterion","authors":"Yi Liu ,&nbsp;Chao Hu ,&nbsp;Sheng Chen ,&nbsp;Weixin Qiu ,&nbsp;Jian Zhang","doi":"10.1016/j.seta.2024.104105","DOIUrl":"10.1016/j.seta.2024.104105","url":null,"abstract":"<div><div>The flow characteristics of water columns in pressurized piping systems significantly influence the stability of pumped-storage power stations (PSPSs). However, the complex mathematical representation of the elastic water column often leads to its simplification to a rigid column in stability analyses. This study established elastic and rigid models of a PSPS system based on elastic and rigid water columns, respectively. The stability regions of the governor parameters for these two models were determined and compared. Results indicate that the stability region of the elastic model is smaller than that of the rigid model. Consequently, using a simplified rigid model to evaluate the stability of an actual elastic system would pose potential instability risks. Furthermore, the primary cause of the stability difference between the elastic and rigid models is identified as the water hammer wave velocity. As the wave velocity increases, the stability region of the elastic model expands, eventually approaching that of the rigid model. Lastly, the coupling mechanism between the pressurized pipe and the pumped-storage unit is clarified. The modulus of the water hammer reflection coefficient is proposed to quantify the stability performance of the pumped-storage unit. These findings provide crucial insights for ensuring the stable operation of PSPSs.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104105"},"PeriodicalIF":7.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review of life cycle assessment of renewable agricultural systems","authors":"Mohammadali Kiehbadroudinezhad ,&nbsp;Homa Hosseinzadeh-Bandbafha ,&nbsp;Sheikh Ahmad Faiz Sheikh Ahmad Tajuddin ,&nbsp;Meisam Tabatabaei ,&nbsp;Mortaza Aghbashlo","doi":"10.1016/j.seta.2024.104100","DOIUrl":"10.1016/j.seta.2024.104100","url":null,"abstract":"<div><div>Integrating renewable energy technologies into agriculture offers a promising approach to significantly reducing carbon emissions. Agriculture is inherently energy-intensive, with substantial reliance on fossil fuels for various operations, including machinery, irrigation, heating, cooling, and processing. However, these systems come with their own environmental impacts and sustainability challenges, making it critical to understand their overall effect on the environment. Life cycle assessment (LCA) is vital for analyzing these impacts. Despite introducing some uncertainties, LCA methodologies provide a structured approach for examining every phase of the life cycle of a product, empowering stakeholders to identify areas for improvement and make informed decisions. This paper reviews the environmental opportunities and limitations of integrating renewable energy systems into agriculture, focusing on LCA analysis. Renewable systems integrated with farming show the potential to reduce emissions and fossil energy demand. However, many studies focus primarily on energy production, often overlooking significant environmental impacts. Critical data, such as the disposal of hazardous materials, wind turbine noise, and land use for energy crops, are frequently omitted, leading to potentially biased results. LCA research often focuses primarily on carbon emissions and global warming, frequently highlighting renewable energy technologies as sustainable solutions. Yet, there is insufficient focus on human health impacts, particularly the toxicity of substances like heavy metals released during various stages, from production to disposal and recycling. Addressing waste management challenges associated with renewable energy systems is essential to ensuring long-term environmental integrity in agriculture. Future research should aim to fill these gaps by conducting more comprehensive assessments, including the impacts on ecosystems and human health throughout the entire lifecycle of renewable energy systems in farming. Innovation is also needed to improve recycling and waste management of renewable energy components, along with advancing energy storage and decentralized systems in agriculture, with LCA serving as a guiding tool for identifying the most sustainable solutions. Finally, integrating life cycle costing and social LCA is vital for assessing the broader sustainability of renewable energy adoption in agriculture.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"73 ","pages":"Article 104100"},"PeriodicalIF":7.1,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}